• No results found

Characterization of Intestinal and Hepatic CYP3A-Mediated Metabolism of Midazolam in Children Using a Physiological Population Pharmacokinetic Modelling Approach

N/A
N/A
Protected

Academic year: 2021

Share "Characterization of Intestinal and Hepatic CYP3A-Mediated Metabolism of Midazolam in Children Using a Physiological Population Pharmacokinetic Modelling Approach"

Copied!
13
0
0

Loading.... (view fulltext now)

Full text

(1)

RESEARCH PAPER

Characterization of Intestinal and Hepatic CYP3A-Mediated Metabolism of Midazolam in Children Using a Physiological Population Pharmacokinetic Modelling Approach

Janneke M. Brussee1& Huixin Yu1,2& Elke H. J. Krekels1& Semra Palić1,3& Margreke J. E. Brill4& Jeffrey S. Barrett5,6&

Amin Rostami-Hodjegan7,8&Saskia N. de Wildt9,10&Catherijne A. J. Knibbe1,11

Received: 6 February 2018 / Accepted: 9 July 2018 / Published online: 30 July 2018

# The Author(s) 2018

ABSTRACT

Purpose Changes in drug absorption and first-pass metabo- lism have been reported throughout the pediatric age range.

Our aim is to characterize both intestinal and hepatic CYP3A-mediated metabolism of midazolam in children in order to predict first-pass and systemic metabolism of CYP3A substrates.

Methods Pharmacokinetic (PK) data of midazolam and 1-OH- midazolam from 264 post-operative children 1–18 years of age after oral administration were analyzed using a physiological pop- ulation PK modelling approach. In the model, consisting of phys- iological compartments representing the gastro-intestinal tract and liver,intrinsic intestinal and hepatic clearances were estimated to derive values for bioavailability and plasma clearance.

Results The whole-organ intrinsic clearance in the gut wall and liver were found to increase with body weight, with a 105

(95% confidence interval (CI): 5–405) times lower intrinsic gut wall clearance than the intrinsic hepatic clearance (i.e. 5.08 L/

h (relative standard error (RSE) 10%)versus 527 L/h (RSE 7%) for a 16 kg individual, respectively). When expressed per gram of organ, intrinsic clearance increases with increasing body weight in the gut wall, but decreases in the liver, indicat- ing that CYP3A-mediated intrinsic clearance and local bio- availability in the gut wall and liver do not change with age in parallel. The resulting total bioavailability was found to be age-independent with a median of 20.8% in children (95%CI: 3.8–50.0%).

Conclusion In conclusion, the intrinsic CYP3A-mediated gut wall clearance is substantially lower than the intrinsic hepatic CYP3A-mediated clearance in children from 1 to 18 years of age, and contributes less to the overall first-pass metabolism compared to adults.

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11095-018-2458-6) contains, which is available to authorized users.

* Catherijne A. J. Knibbe c.knibbe@antoniusziekenhuis.nl Janneke M. Brussee

brusseejm@lacdr.leidenuniv.nl

1 Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research (LACDR), Leiden University, Leiden, the Netherlands

2 Present address: Novartis, Basel, Switzerland

3 Present address: Netherlands Cancer Institute (NKI), Amsterdam the Netherlands

4 Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden

5 Translational Informatics, Sanofi, Bridgewater, New Jersey, USA

6 Department of Pediatrics, Division of Clinical Pharmacology &

Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA

7 Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, UK

8 Simcyp Limited (A Certara Company), Sheffield, UK

9 Intensive Care and Department of Pediatric Surgery, Erasmus MC - Sophia Children’s Hospital, Rotterdam, the Netherlands

10 Department of Pharmacology and Toxicology, Radboud University Medical Centre, Nijmegen, the Netherlands

11 Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein the Netherlands

(2)

KEY WORDS CYP3A . extraction ratio . absorption . first-pass metabolism . gut wall . liver . pediatrics

INTRODUCTION

Differences in drug absorption and first-pass metabolism have been reported in children compared to adults (1–3). These differences may for instance result from a smaller intestinal surface area in children (2) and altered permeability across age (1). In addition, besides gastric emptying time, intestinal transit time, the production of bile fluid (3) and organ blood flow to intestines and liver that may be altered in children (4), intestinal and hepatic drug metabolizing enzyme activity may be different from those in adults. For first-pass metabolism, the activity of both intestinal and hepatic enzymes is of relevance, while for systemic clearance the activity of hepatic enzymes is important with activity of intestinal enzymes probably being of negligible influence.

With cytochrome P450 (CYP) being an enzyme family in- volved in metabolism of many drugs (5), this study focuses on CYP3A enzymes, as they are abundant in both intestine and liver (6,7). From the available in vitro and in vivo studies on the ontogeny of CYP3A in children (8–10), there is some evidence that the maturation and regulation of these enzymes in the gut wall and liver may differ (11). However, the translation of en- zyme activity in gut wall and liver to intestinal and hepatic clearance is complex, because other parameters like organ blood flow, organ size and other physiological parameters need to be taken into account (4,12). In order to distinguish between intestinal and hepatic clearance (and their maturation), a com- bination of mechanistic and empirical models can be useful, as was shown in adults before (13,14). This hybrid of approaches seems necessary as for full physiologically-based PK models in children not all parameters are always available and/or iden- tifiable, while empirical models may lack direct physiological interpretation. The latter is particularly problematic, because both hepatic and intestinal metabolism contribute to first-pass metabolism. As such, the combination of PBPK concepts with population modelling using PK data from children enables incorporation of prior knowledge of the system, while obtaining more insight into the system by parameter estimation based on reverse translation of the observed clinical data (15).

In this study, the aim is to characterize both intestinal and hepatic CYP3A-mediated metabolism of midazolam in chil- dren between 1 and 18 years of age. We will adopt the above described physiological population PK modelling approach, in which we account for known changes in the physiology of the gastrointestinal tract, and use the available PK data from the population, to estimate the whole-organ intrinsic intestinal and hepatic CYP3A-mediated midazolam clearance in chil- dren. For this analysis, we had access to data from a clinical study in which the CYP3A substrate midazolam which is

considered a probe drug for CYP3A (16), was administered to children pre-operatively, and in which both midazolam and the CYP3A-mediated metabolite (i.e. 1-OH-midazolam) con- centrations were available.

METHODS

Data

In 873 plasma samples from 266 patients of the Children’s Hospital of Philadelphia, PA, midazolam and 1-OH- midazolam concentrations were measured (17). The children received a median dose of 10 mg (range 3–15 mg) of midazo- lam as oral suspension pre-operatively. Subjects include chil- dren (150 boys/116 girls) between 1 and 18 years of age (me- dian 7 years), with a median body weight of 27.2 kg (range 9.1–137.6 kg), who fit the criteria I or II of the American Society of Anesthesiologist’s (ASA) classification, undergoing surgery. In 31 patients, midazolam and its primary metabolite were densely sampled around 0.25, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 10 and 22 h after dose administration with a median of 10 sam- ples per patient (range 8–11), and in 235 patients, samples were sparsely collected for analysis at different time points post-dose (median 2, range 1–3 samples/patient) with most samples within the first four hours after dose administration (figureS1). Data from two 14-year old patients in the sparsely sampled group were excluded as their body weight was

<12 kg. The patient groups who were in the dense and sparse sampled study were comparable in age and weight distribu- tion (TableSI). Patient height and body surface area, required for some of the covariate relationships in the model, were derived from recorded age and body weight information (equations in supplemental material).

Blood concentrations (B) were estimated based on the mea- sured plasma concentrations (P) using eq.1(18):

B: P ¼ 1 þ Hem  f u Kp−1

ð1Þ

In which Hem is the hematocrit based on population values reported in literature (19) ranging from 0.36 in 1- and 2-year- old infants up to 0.41–0.43 in adolescents of 12–18 years of age (TableI), the fuis the fraction unbound in plasma and Kp

is the unbound partition coefficient of the red blood cells to plasma (assumed to be constant between adults and children) (18). The fraction unbound in plasma for both midazolam and 1-OH-midazolam were calculated based on the formula of McNamara and Alcorn (20):

fu;pediatric¼ 1

1þ1−fu;adult

 P½ pediatric

½ P adult fu;adult

ð2Þ

(3)

where fu,pediatricand fu,adultare the fraction unbound of the drug in plasma for children and adults respectively and [P]pediatricand [P]adultare the plasma albumin concentrations in children and adults respectively, assuming exclusive binding to albumin for midazolam and its metabolite. The fractions unbound of midazolam and 1-OH-midazolam in plasma in adults were reported in literature (21,22). The albumin con- centrations [P]pediatricare calculated based on the formula of

Johnson et al. (12):

½ Ppediatric½g=L ¼ 1:1287  ln Age yrð ½ Þ þ 33:746 ð3Þ

Measurements below the lower limit of quantification were discarded according to the M6 method (23) (n = 4 (0.5%) and n = 5 (0.6%) of midazolam and 1-OH-midazolam measure- ments respectively).

Table I Parameter Values for System Specific and Drug Specific Parameters Included in the Physiological Population PK Model

Parameter name (unit) Parameter symbol Formula for calculation Value References

Tissue volumes (L)

Liver Vh 0.722 × BSA1.176 (25)

Portal vein Vpv 0.0052 (26)

Small intestine Vin 0.0467 × age + 0.0901 (4)

Tissue blood flows (L/h)

Cardiac output CO BSA × (110 + 184.974 × (e-0.0378 × age

- e-0.24477 × age

)) (27)

Hepatic blood flow Qh 0.28 × CO (♀)

0.255 × CO (♂) (27)

Portal vein Hepatic artery

Qpv

Qha

0.75 × Qh

0.25 × Qh

(12,52)

Small intestine Mucosa Microvilli

Qin

Qmuc

Qvilli

0.4 × Qh

0.8 × Qin

0.6 × Qmuc

(30,49)

Plasma proteins

Plasma albumin concentration (g/L) Ppediatric

Padult

1.1287 × ln(age) + 33.746 -

37.7

(12)

Hematocrit (%) Hem1-2y

Hem3-6y

Hem7-12y

Hem12-18y,♀

Hem12-18y,♂

0.36

0.37 0.40 0.41 0.43

(19)

Midazolam

Fraction absorbed Fa 1 (29)

Absorption rate constant (h−1) Ka 4.16

Blood: plasma ratio B:P ratio 1 = [Hem × (fu×Kp− 1)]with Kp= 1 (18)

Fraction unbound in gut Fu,G 1

Fraction unbound in plasma Fu,plasma

Fu,adult

1 1þð1− f u;adultÞ P½ pediatric

½ adult  f u;adultP

0.0303 (20) (21) Permeability through the enterocyte (L/h) CLperm CLperm= Peff,man× A with Peff,man= 4.4 × 10−4cm/s (30) Intestinal surface area (dm2) A 2πr(r + h) with radius r = ½ × (0.016 × BSA + 0.0159)

and length h = 2.56 × BSA + 2.95

(12)

1-OH-midazolam

Blood: plasma ratio B:P ratio B : P = 1 + [Hem × (fu, M×Kp− 1)] with Kp= 1 (18) Fraction unbound in plasma Fu,M,pediatric

Fu,M,adult

1 1þð1− f u;M;adultÞ P½ pediatric

½ adult  f u;M;adultP

0.106 (20) (22)

Age is expressed in years. A is the intestinal surface area in dm2. BSA is the body surface area in m2. Peff,manis the effective intestinal permeability per unit surface area (dm/h). WT is body weight in kg

♀ female, ♂ male

(4)

MODEL DEVELOPMENT

Structural Model

The physiological population PK analysis was performed using NONMEM version 7.3 (ICON, Globomax LLC, Ellicott, MD, USA) based on first-order conditional esti- mation with interaction, and for visualization of data Pirana 2.9.0, R (version 3.3.1), and R-studio (version 0.98.1078) were used. A physiological population phar- macokinetic (PK) model, earlier developed and applied by Yang et al. (24), Frechen et al. (13) and Brill et al. (14) to describe midazolam PK data in adults, was now ap- plied to describe the midazolam PK data in children 1–

18 years of age (Fig. 1). This model includes physiologi- cal compartments representing the gut wall, the portal vein and the liver, and also empirical central and periph- eral compartments for midazolam and 1-OH-midazolam distribution, representing the blood circulation and fast equilibrating tissue, and peripheral slow equilibrating tis- sues (13,24). Based on literature, central and peripheral volumes were linearly scaled based on body weight from a 76 kg healthy adult with volumes of 20.4 L/76 kg, 55.2 L/76 kg and 79.1 L/76 kg for the central and two peripheral volumes for midazolam respectively and with a volume of 65.7 L/76 kg for 1-OH-midazolam

(13). The fraction midazolam metabolized into 1-OH- midazolam was assumed 100% (Table II).

In the physiological compartments, tissue volumes and blood flows in children were based on literature data. The hepatic volume (Vh) was calculated based on body surface area (BSA, m2) (25):

Vh½  ¼ 0:722  BSAL 1:176 ð4Þ

Volume of the portal vein was assumed to be equal to the reported value of 5.2 mL in adults (26). To calculate the vol- ume of the intestines, a regression line was derived from data published by Björkman (4):

Vin½  ¼ 0:0467  Age yL ½  þ 0:0901 ð5Þ To calculate organ weight, the organ volumes are multi- plied by the organ density of 1040 g/L (4). To compare with adult values, organ weight in adults is calculated assuming organ volumes of 1 L (13) and an organ density of 1040 g/L.

The hepatic blood flow (Qh) was assumed to be a fixed percentage of the cardiac output (CO), which was calculated based on BSA (27):

CO¼ BSA  110 þ 184:974  e0:0378  agee0:24477  age  

ð6Þ

Fig. 1 Schematic representation of the physiological population PK model for midazolam and the metabolite 1-OH-midazolam. The extraction of midazolam is defined by the well-stirred model in the liver and the‘Qgut’ model in the gut wall. E = extraction ratio, F = bioavailability in the gut wall (gut, G) and the liver (hepatic, H). CLintis the whole-organ intrinsic clearance in the gut wall and liver, Ka indicates the absorption rate constant and the fraction unbound in blood and gut wall are described with fu,Band fu,Grespectively. Blood flows are represented by Q; in the micro villi (Qvilli), portal vein (QPV), hepatic artery (QHA) and liver (Qh). Distribution between central and peripheral (Periph.) compartments is estimated by inter-compartmental clearance Q1and Q2for the two peripheral compartments for midazolam. Parameters describing the metabolite are indicated with the subscript M.

(5)

Other tissue blood flows were assumed to be propor- tional to the hepatic blood flow (Table I). The relation- ship between plasma protein binding, intestinal surface area, tissue volumes, and organ blood flows and body weight for the individual patients in this study are depicted in figureS2. For all physiological parameters in Table I, population values were used without inter- individual variability or uncertainty.

The absorption rate constant (ka) for midazolam could not be estimated, and was therefore fixed at 4.16 h−1, yielding peak concentrations to be reached round 30 min (tmax), which is in agreement with the observed tmax and other reported literature values (28). The oral bioavailability (Ftotal) was cal- culated using:

Ftotal¼ Fa Fg Fh ð7Þ

in which Fais the fraction absorbed, which is assumed 1 for midazolam (29), Fgis the gut wall bioavailability, equal to 1 minus the gut wall extraction ratio (Eg), and Fhis the hepatic bioavailability, which is equal to 1 minus the hepatic extrac- tion ratio (Eh). The hepatic extraction ratio of midazolam (EH) and 1-OH-midazolam (EH,M) were defined by the well-stirred model:

EH ¼ CLH;int fu;B

Qhþ CL H;int fu;B ð8Þ

where CLH,int is the estimated intrinsic hepatic clearance (whole-organ), fu,Bis the fraction unbound in the blood and Qhis the hepatic blood flow. The gut wall extraction ratio is described using the Qgut model (30):

EG¼ CLG;int fu;G

Qgutþ CLG;int fu;G

  ð9Þ

Where CLG,intis the estimated intrinsic gut wall clearance (whole-organ), fu,Gis the fraction unbound in the gut, which was assumed to be 1, and Qgutis the effective blood flow at the gut wall (30) which is defined by:

Qgut¼Qvilli CLperm

Qvilliþ CLperm ð10Þ

In which Qvilliis the villous blood flow and CLpermis the permeability through the enterocytes of the gut wall for the drug. This permeability factor depends on the effective intestinal permeability per unit surface area (30) (Table I) and the intestinal surface area A described by eq.12, and can be calculated using eq.11.

CLperm¼ Peff;man A ð11Þ

With A¼ 2πr r þ hð Þ ð12Þ

where r is the intestinal radius in meters and h the intestinal length in meters, which are both calculated using a BSA-based formula (eqs.13and14) (12):

r¼ §  0:016  BSA þ 0:0159ð Þ ð13Þ

h¼ 2:56  BSA þ 2:95 ð14Þ

The total intestinal surface area was cut-off at a maximum value of the adult value of 0.66 m2(30) (figureS2). The total plasma clearance was calculated using eq.15:

CLplasma¼ Qh CLH;int fu

Qhþ fu CLH;int

= B : P ratioð Þ ð15Þ

Where Qh is the hepatic blood flow, CLH,int is the estimated intrinsic hepatic clearance, fu is the fraction unbound in plasma, and B:P ratio is the blood-to- plasma ratio of midazolam.

Statistical Model

Inter-individual variability in the estimated intrinsic clearance parameters for midazolam and 1-OH-midazolam was includ- ed in the model using the following equation:

CLint;i ¼ θTV  eηi ð16Þ

In which CLint,iis the individual intrinsic clearance esti- mate for individual i,θTVis the typical value of the intrinsic clearance in the studied population andηiis a random vari- able for the ith individual form a normal distribution with a mean of zero and variance ofω2, yielding a log-normal distri- bution for the parameter value in the population. Inter- individual variability in the estimated intercompartmental clearance parameters (Qcp1and Qcp2) for midazolam was in- cluded as well.

Residual unexplained variability was modelled using a combined proportional and additive error model for both midazolam and 1-OH-midazolam. The jth ob- served concentration Y of the ith individual was modelled according to:

Yij¼ Cpred;ij 1 þ ε1ij

þ ε2ij ð17Þ

where Cpred,ij is the jth predicted midazolam concentra- tion of the ith individual, ε1ij and ε2ij are random var- iables from a normal distribution with a mean of zero and variance of σ2.

Covariate Analysis

A covariate analysis for the estimated parameters (whole- organ intrinsic clearance (CLG,int, CLH,int, CLH,int,M) and

(6)

intercompartmental clearance (Qcp1, Qcp2)) was per- formed in which the following covariates were tested for significance: age, body weight, height, body surface area, and sex. For sex, the typical value (θTV) for girls was estimated relative to the value for boys. The remaining continuous covariates were tested using a power (Eq.18) or linear (Eq.19) function.

Pi¼ θTV  COV COVmed

 θCOV

ð18Þ

Pi¼ θTV 

1þ θcov COV −COVð medÞ ð19Þ where Piis individual parameter estimate for individual i,θTV

the typical value of the parameter in the studied population with a median value (COVmed) of the covariate (COV) and θCOVthe estimated exponent or slope for a power or linear function respectively.

Model Evaluation

Structural models were evaluated by comparison of the objec- tive function values (OFV, i.e. -2 × log-likelihood). A decrease of 3.84 in the OFV between nested models (p < 0.05) was considered statistically significant. In addition, goodness-of- fit plots of midazolam and 1-OH-midazolam were assessed, in which observed versus individual- and population-predicted concentrations and conditional weighted residuals (CWRES) versus time and population predicted concentrations are visu- alized. Moreover, the condition number, the confidence inter- val of the parameter estimates, and visual improvement of the individual plots were used to evaluate the models.

For inclusion of covariates, a drop in OFV by at least 6.64 points (p < 0.01) was considered statistically significant, while for the backward deletion a more stringent p value (p < 0.005, ΔOFV>7.88) was used. Moreover, to retain a covariate in the model, the inter-individual variability in the PK parameter should decrease.

Two methods were applied to evaluate the final model internally. A bootstrap analysis (n = 250) was performed to evaluate model stability and parameter precision (31). In ad- dition, a normalized prediction distribution error (NPDE) analysis was performed using the NPDE package in R (32).

For each observed concentration, 1000 midazolam concen- trations were simulated based on the parameter values that were obtained for the original model (TableII). The observed concentrations were compared to the range of 1000 predicted concentrations. The Wilcoxon signed rank test was used to assess the deviation of the observed mean value of the NPDE to the expected value of 0, and the Fisher variance test was used to assess the deviation of the observed variance from the expected value of 1.

Sensitivity Analysis

A sensitivity analysis was performed to evaluate the assump- tions made in the model. For this, it was evaluated what the impact was of a 50% increase or decrease of the parameter values for intestinal length, the fraction unbound and tissue volumes and blood flows on predicted midazolam concentra- tions and on the estimated model parameters. Additionally, the impact of the assumed fraction absorbed (Fa) of 1 (29), on the estimated whole-organ intrinsic clearance in the gut wall and liver, and the derived total plasma clearance, was evalu- ated, as well as a 50% increase or decrease of volume of distribution of the primary metabolite, 1-OH-midazolam.

RESULTS

In the model as shown in Fig.1, the intrinsic gut wall clearance was 5.08 L/h (with a relative standard error (RSE) of 16%) and the intrinsic hepatic clearance was 527 L/h (RSE 7%) for a typical individual of 16 kg (TableII). The increase in these whole-organ intrinsic clearance values, reflected by the inclu- sion of a power function (eq.18) correlating body weight as covariate to intrinsic clearance with an exponent of 0.807 (RSE 10%) and 0.472 (RSE 16%) for intestinal and hepatic maturation respectively, appeared to be slightly larger in the gut wall than in the liver (TableII). For intercompartmental clearance of midazolam to the first peripheral compartment (with Vp1= 55.2 L), body weight was found as a covariate, while no covariate was identified for intercompartmental clearance to the second peripheral compartment (with Vp2= 79.1 L). Lastly, a covariate was included in the model correlating weight to intrinsic hepatic clearance of the metab- olite with an exponent of 0.651 (RSE 9%). Age, height, body surface area, and sex were not identified as covariates for the estimated parameters. The gut wall metabolism of the metab- olite could not be estimated independently due to model in- stability, and was therefore estimated as a fraction of the gut wall metabolism of midazolam. The bootstrap results con- firmed the model stability and the precision of parameter es- timates of the model (TableII).

Figure2a illustrates the relation between body weight and whole-organ intrinsic clearance in the gut wall and the liver.

As illustrated in this figure, the intrinsic hepatic clearance was estimated to be around 105 times higher than the intrinsic gut wall clearance for a typical individual of 16 kg, while this factor differed largely between individuals (factor of 5–405, 95%CI). When the gut wall and hepatic intrinsic clearances are expressed per gram of organ, an inverse trend can be observed for hepatic intrinsic CYP3A activity per gram of organ. In Fig.2b, the intrinsic clearance per gram of organ are plotted versus age, which shows a (slight) decrease in hepatic intrinsic CYP3A activity per gram of liver with age, while no

(7)

change with age is observed for gut wall intrinsic CYP3A activity per gram of small intestine except for a small drop around the age of 4–5 years.

Using eq.15, the total plasma clearance was derived and plotted against body weight, showing that total plasma clear- ance also increases with body weight (Fig.3). For comparison, in Fig.2a, band3, literature values on whole-organ intrinsic and total plasma clearance in adults have been added (13).

Using the estimated whole-organ intrinsic clearance values, together with blood flow and fraction unbound, the extraction ratios Egand Eh(eqs.8and9) and bioavailability values Fg

and Fh(i.e. 1-Eg or Eh, respectively) were derived. Figure4 shows the results with gut wall bioavailability first slightly in- creasing and then decreasing with age, while the hepatic bio- availability showed an overall increase with age. More specif- ically, the hepatic bioavailability is increasing with body weight from a median of 58% (range 35–79%) to 73% (range 58–86%) from 1 to 2 year old to children 12–18 years of age (p < 0.001, Wilcoxon-Mann-Whitney U-test) (Fig.4). With re- spect to the gut wall bioavailability, the median of 37% (range 8–85%) in 1–2 year old children increases to 39% (range 6–

82%) in children of 3–5 years of age, then to decrease to 34%

Table II Parameter Estimates of the Final Physiological Population PK Model

Parameter definition Parameter (unit) Value (RSE%)

[shrinkage %]

Bootstrap median

Bootstrap 90% CI 70-kg individual Midazolam

Intrinsic hepatic clearance CLH,int,i= CLH,int,16kg× (WT/16)k1 CLH,int,16kg(L/h) 527.0 (7%) 601.4 523.5–748.6 1057

Exponent k1 0.472 (16%) 0.425 0.206–0.554 0.472

Intrinsic gut wall clearance CLG,int,i= CLG,int,16kg× (WT/16)k2 CLG,int,16kg(L/h) 5.08 (10%) 4.93 3.32–6.17 16.7

Exponent k2 0.807 (10%) 0.881 0.622–1.27 0.807

Volume of distribution (central) Vc,i= Vc,76kg× (WT/76)k3 Vc,76kg(L) 20.4 fix 18.8 Volume of distribution (two peripheral compartments)

Vp,i= Vp,76kg× (WT/76)k3

Vp1,76kg(L) Vp2,76kg(L)

55.2 fix 79.1 fix

- -

50.8

72.9

Exponent k3 1 fix 1

Inter compartmental clearance Qcp1,i= Vcp1,16kg× (WT/16)k4 Qcp1(L/h) 14.9 (19%) 14.9 8.9–25.9 57.9

Exponent k4 0.92 (21%) 1.03 0.796–1.65 0.92

Inter compartmental clearance (2nd peripheral compartment) Qcp2(L/h) 7.5 (10%) 7.7 6.3–11.2 7.5 1-OH-midazolam (M)

Fraction midazolam metabolized into 1-OH-midazolam fM 1 fix 1

Intrinsic hepatic clearance CLH,int,M,i= CLH,int,M,16kg× (WT/16)k5 CLH,int,M,16kg(L/h) 235.0 (6%) 236.2 219.6–269.6 614.2

Exponent k5 0.651 (9%) 0.615 0.451–0.750 0.651

Intrinsic gut wall clearance CLG,int,M,i= k6 × CLG,int,i

k6 18.4 (12%) 19.2 10.6–198.2 18.4

Volume of distribution VM,i= VM,76kg× (WT/76)k7

VM,76kg(L) 65.7 fix 60.5

Exponent k7 1 fix 1

Inter individual variability (variance)

Intrinsic hepatic clearance ω2CLH,int 0.25 (13%)[25%] 0.24 0.16–0.32

Intrinsic gut wall clearance ω2CLG,int 1.20 (13%)[13%] 1.25 1.04–1.56

Inter compartmental clearance ω2Qcp1 1.05 (35%)[42%] 1.05 0.26–1.85

ω2Qcp2 1.06 (31%)[46%] 1.06 0.68–1.79

Intrinsic hepatic clearance 1-OH-midazolam (M) ω2CLH,int,M 0.13 (18%)[31%] 0.13 0.08–0.19 Residual variability (variance)

Proportional error (Midazolam) 0.166 (8%)[19%] 0.169 0.150–0.199

Additive error (Midazolam), nmol/L 0.001 fix

Proportional error (1-OH-midazolam) 0.292 (11%)[9%] 0.271 0.225–0.309

Additive error (1-OH-midazolam), nmol/L 0.528 (10%)[9%] 0.454 0.130–0.826

RSE: relative standard error. CI: the 5th–95th percentiles are shown, indicating a 90% confidence interval. Bootstrap n = 250. Inter-individual and residual variability values are shown as variance estimates. Intrinsic clearance values are reported for the whole organ

(8)

(range 3–84%) and 29% (range 4–66%) in children of 6–12 and 12–18 years of age, respectively. With total bioavailability being equal to Fgtimes Fh(eq.7), Fig.4shows that no or only small changes in the total bioavailability for children up to 12 years of age can be expected. In adolescents, the gut wall, hepatic and total bioavailability proved not significantly dif- ferent from the values observed in adults which were obtained from literature (p > 0.05).

FigureS3shows the goodness-of-fit plots of both midazo- lam and its primary metabolite. These plots for midazolam indicated no bias for midazolam in the individual and popu- lation concentration predictions versus the observed concentra- tions (figureS3A,B) and no trend or bias in the conditionally weighted residuals versus the predicted concentrations or time after dose (figureS3C,D). Also the presystemic formation of

1-OH-midazolam was well described by the model, as except for a small under prediction of the peak concentrations (figure S3E), no bias in the goodness-of-fit plots for the metabolite was observed (figureS3E-H). The normalized prediction dis- tribution error (NPDE) results showed no bias in the concen- tration predictions for both midazolam and 1-OH-midazolam (figureS4), indicating no structural model misspecification.

The variance of midazolam concentrations however was under-estimated in our model (Fisher variance test, p <

0.001), while the model adequately captures the variability for 1-OH-midazolam concentrations.

The sensitivity analysis (table SII) showed that changing volumes of the gut wall or liver by 50% does not considerably impact the predicted concentrations (<10%) nor our param- eter estimates for whole-organ intrinsic clearance for gut wall and liver. With a 50% increase or decrease in hepatic blood flow, the whole-organ intrinsic hepatic clearance inversely changes with−14% and + 49% respectively. A similar trend was found for intestinal blood flow and intestinal length (table SII). A change in fraction unbound in blood resulted in a change in whole-organ intrinsic hepatic clearance by the same factor. If the fraction midazolam that gets absorbed (Fa) is smaller than 100%, the median total bioavailability does not change considerably. While the hepatic bioavailability is not impacted, the gut wall bioavailability however increases by 4.1 and 18.7% for an Faof 0.90 and 0.80, respectively. A change in the volume of distribution of the primary metabolite leads to considerable changes in all clearance parameters. All results of the sensitivity analysis are summarized in the supplemental material (tableSII).

Fig. 2 First-pass metabolism parameters in children. (a) Intrinsic whole- organ intestinal (■) and hepatic (○) clearance versus body weight, both indi- vidually predicted (symbols) and the population predictions (lines) for children in our study. Also illustrated are the reported literature values of 26.7 and 1640 L/h for intestin al ( ) and hepatic ( ) clearance in adults, respectively (13). (b) Intrinsic gut wall (■) and hepatic (○) clearance per gram of organ versus age for children in our study and for adults(), both individually predict- ed (symbols) and a loess curve of the population predictions (lines) for children in our study.

Fig. 3 Total hepatic plasma clearanceversus body weight for children in our study (○) and calculated plasma clearance in adults ( ) based on the reported typical hepatic whole-organ intrinsic clearance of 1640 L/h, a hepatic blood flow increasing with body weight (Qh= 3.75∙WT0.75), a fraction unbound of 0.0303 and a blood: plasma ratio of 0.66 (13) using eq.15.

(9)

DISCUSSION

To characterize both intestinal and hepatic CYP3A-mediated metabolism of midazolam in children between 1 and 18 years of age, a physiological population PK model was developed (Fig.1). The physiological population PK modelling approach we applied has been previously applied in healthy adults (13) and morbidly obese versus bariatric surgery patients (14), and this approach has now proven useful in distinguishing between metabolism by intestinal and hepatic CYP3A enzymes in chil- dren as well.

Using PK data from one of the few clinical studies in which children varying in age between 1 and 18 years old received midazolam orally (17), we showed that the whole-organ in- trinsic clearance of gut wall and liver do not change in parallel (Fig.2a). For all pediatric ages, the intrinsic hepatic clearance is higher than the intrinsic gut wall clearance, while the gut wall clearance appears to increase slightly faster than hepatic clearance (Fig. 2a). The estimated clearance values for the patients with the highest body weight (>16 years of age) are with 16.1 L/h and 1051 L/h in the same order of magnitude as the reported values of 26.7 L/h and 1640 L/h for intrinsic intestinal and hepatic clearance in adults respectively (13). As we used the whole-organ intrinsic clearance of midazolam as surrogate marker of total hepatic and intestinal CYP3A activ- ity in this study, we found that the total intestinal CYP3A activity is lower than the hepatic CYP3A activity. However, when expressed per gram of organ, no increase in intrinsic gut wall clearance per gram of organ can be observed, while the intrinsic hepatic clearance per gram of liver is highest in the youngest children and decreases with age (Fig.2b).

The increase in whole-organ intrinsic clearance in the gut wall we report here can be mostly attributed to the organ growth and the increasing total weight of the enterocytes in children (33,34), as per gram of gut wall no trend with increas- ing age (Fig.2b) or body weight can be observed in children

>2 year of age. The intrinsic intestinal CYP3A4 expression per gram of small intestine in children has been described to be slightly higher in children <2 years of age, compared to 2–

5 year old children, and then increases with age (33). This is in agreement with the small drop in gut wall intrinsic CYP3A activity per gram of small intestine we observe around the age of 4–5 years (Fig. 2b), and in combination with the other physiological changes this leads to a higher gut wall bioavail- ability in children 3–5 year of age compared to children 1–

2 years of age, and a decrease in gut wall bioavailability with increasing age in children >3 years of age, which is in agree- ment with the trend observed in Fig.4.

We report the whole-liver intrinsic hepatic CYP3A- mediated metabolism to increase with increasing body weight, which can be attributed to an increasing total liver weight (4).

In literature, the amount of microsomal protein in the liver is believed to remain constant with age (35), while the CYP3A4

abundance per gram of microsomal protein (8,36) has been reported to increase with age. Our results however show a slight decrease in intrinsic clearance per gram of liver through- out the pediatric age range, suggesting that the absolute abun- dance or activity of CYP3A4 per gram of liver slightly de- creases with age in children 1–18 years of age.

The extraction ratios Egand Ehcan be derived from the estimated whole-organ intrinsic clearance, the organ blood flows and the fraction unbound (Eqs.8 and 9), and can be subsequently used to calculate the bioavailability (i.e. Fgand Fh). The fraction escaping gut wall metabolism was found to be smaller (median Fg0.34, range 0.02–0.85) than the fraction escaping hepatic metabolism (median Fh0.66, range 0.35–

0.93). These values for hepatic bioavailability are in agree- ment with previously reported values in adults (13,37). The median hepatic bioavailability increases with body weight due to a smaller increase in whole-organ intrinsic hepatic clear- ance relative to the hepatic blood flow (Fig.4), while an in- verse, but smaller age-related trend in median intestinal bio- availability was found as the effective blood flow in the gut wall (Qgut) increases less with age than the whole-organ intrin- sic intestinal clearance.

In adults, the local bioavailability in the gut wall is much lower than in the liver with reported values for Fg and Fh

around 0.2 and 0.7, respectively (13), and therefore in adults the extraction ratio in the gut wall is higher than in the liver, indicating that intestinal CYP3A enzymes play a large role in presystemic metabolism despite the low whole-organ intrinsic clearance. In children, the intrinsic gut wall CYP3A activity is lower than in adults (Fig.2a), and together with a lower effec- tive blood flow, this leads to a higher gut wall bioavailability compared to adults (Fig.4). This indicates that the role of gut wall metabolism in presystemic metabolism is smaller in chil- dren compared to adults, and also gets smaller with decreasing age. This is compensated by the increased whole-organ intrin- sic hepatic CYP3A-mediated intrinsic clearance (Fig. 2a), which together with the hepatic blood flow leads to lower hepatic bioavailability with decreasing age (Fig.4), resulting in an age-independent total bioavailability Ftotalwith a medi- an value of 20.8% (Fig.4).

The parameters for clearance and total bioavailability are in agreement with literature. For clearance, the plasma clear- ance can be calculated based on the estimated intrinsic hepatic clearance, the fraction unbound, the hepatic blood flow and the blood-to-plasma ratio (eq.15). The derived total plasma clearance of 6.0 L/h in the youngest children of 1–2 years of age to 17.5 L/h in the older children≥16 years of age (Fig.3), is in agreement with literature values of 0.6 L/h/kg (0.56–

0.68 L/h/kg) (28). For patients in the age range between 2 months and 3 years, median clearance values around 9 L/

h have been reported in patients after major craniofacial sur- gery (38) and in patients with severe malaria (39), which is in agreement with our findings. Furthermore, it has been

(10)

reported that disease severity impacts CYP3A-mediated clearance (40), and as the children in this study are rela- tively healthy (ASA criterion I or II), clearance is indeed a factor 2–4 higher than the reported midazolam clearance in critically ill children (40–43).

For bioavailability, the median total bioavailability of 20.8% (mean 22.7 ± 12.4%) across the pediatric age range is similar to the reported median value of 13.4% (13) or the reported mean ± SD of 34.3% ± 10% (37) in adults, but the observed variability in total bioavailability in the children in our study was very large, with values ranging from 1.5–77.9%

A previous study in pediatric patients ranging in age from 6 months to 16 years, who had ASA physical status I-III, found similar values for bioavailability (28) and also found a large variability with the bioavailability ranging from 9 to 71% (28). This high variability has also been described in other studies (44,45), and may be explained by the high unex- plained variability in intestinal CYP3A activity, which may be due to e.g. the circadian rhythm (46), the (genetic) variability in CYP3A5 expression (47), and the different regulation of the gut (11) as a result of exposure to variable food and other environmental effects in different individuals throughout their life (48). This implicates that oral administration will result in highly variable PK profiles and exposure of CYP3A substrates in children, which is relevant in the clinic setting as well as during drug development.

All parameters in the model could be estimated with good precision (RSE < 30%, TableII) and the model stability was evaluated by bootstrap (TableII), which confirmed the preci- sion of the parameter estimates. Furthermore, the goodness- of-fit plots showed that the concentrations of both midazolam and 1-OH-midazolam were well-predicted without bias (figureS3), indicating accurate model predictions for both

the parent compound and the metabolite. FigureS4 shows the normalized prediction distribution errors versus predicted concentrations and versus time after first dose, which demon- strates accurate prediction of the midazolam and 1-OH- midazolam concentrations and variability, with only a small over-prediction of the variability of midazolam.

The model is based on accepted PBPK principles, and well-known equations and parameter values from the litera- ture have been used. For unknown parameter values in the pediatric population, assumptions and scaling methods were applied and a sensitivity analysis was performed for these pa- rameters (TableSII). For hepatic blood flow, the flow was assumed to be a fixed percentage of the cardiac output (25.5% in boys and 28% in girls) (27), which results in blood flow values in agreement with other literature values (49,50).

The sensitivity analysis indicated that if the hepatic or the intestinal blood flow would be 50% higher or lower, that peak concentrations would be impacted, but the derived values for extraction ratio and bioavailability were not impacted by this assumption. Moreover, actual blood flows will likely deviate less than 50% from the assumed flows. The assumed tissue volumes (figureS2C) are in agreement with other literature values (51), and the sensitivity analysis indicated no impact of these assumptions on the results regarding the predicted plas- ma concentrations and the derived values for extraction ratio and bioavailability. Plasma protein binding to albumin has been accounted for in the model (eq. 2), while no protein binding to other plasma proteins was assumed, and the range of fraction bound was with 96.1–96.4% in agreement with the 97.0% protein binding reported in adults (figure S2 A).

Furthermore, our sensitivity analysis indicated that assuming 50% increase or decrease in intestinal length, would lead to +9.3 or− 37.2% change in whole-organ intrinsic gut wall Fig. 4 Bioavailability in in the gut wall (Fg), in the liver (Fh) and total bioavailability (Ftotal) for four different age categories: children of 1–2 years, 3–5 years, 6–

11 years, and 12–18 years of age (increasing dark grey) compared to adult values (13). A nonparametric test of group differences was performed using the independent 2-group Wilcoxon-Mann-Whitney Test, with *** indicating ap-value <0.001, ** for p < 0.01, * for p < 0.05 and ‘NS’ for p > 0.05. Adult bioavailability values are calculated based on their reported typical whole-organ intrinsic hepatic clearance, hepatic blood flow for their body weight and the fraction unbound (see eqs.8and9) (13).

(11)

clearance respectively, without affecting the estimated extrac- tion ratio and bioavailability. This is because the intestinal length impacts the permeability factor of the gut wall and thereby the effective blood flow in the gut wall. Since the amount of drug reaching the systemic circulation is derived from the PK data and does not change, an increase in intes- tinal length is compensated by a decrease in whole-organ in- trinsic gut wall clearance so that the extraction ratio and bio- availability remain constant.

The absorption rate constant could not be estimated in our model, as sampling at early time points was limited and there- fore we included an absorption rate constant of 4.16 h−1, which means that maximum concentrations are reached around 30 min post-dose, which was close to the median ob- served Tmaxand reported values in literature (28). As in this study only oral midazolam was administered, we could not estimate the volume of distribution for midazolam and its metabolite. We therefore linearly scaled the volumes of the central and peripheral compartments from a 76 kg healthy adult (13) to children. The sensitivity analysis showed that the volume of distribution of the metabolite is impacting all estimated clearance parameters considerably (TableSII), but the assumed distribution volumes are in agreement with pre- viously reported values for volume of distribution in children (28,39). Moreover, since we could not estimate inter- individual variability (IIV) in volume of distribution, all inter-individual variability is in the model attributed to the intrinsic clearance parameters and the residual variability, both of which may therefore be inflated.

Furthermore, we assumed that all midazolam is metabo- lized by CYP3A into its primary metabolite, 1-OH-midazo- lam, and the volume and clearance values of the metabolite should therefore be considered as apparent values assuming a 100% formation. As these assumptions on volume of distribu- tion and fraction metabolized are supported by literature (28,39), the PK data of both midazolam and 1-OH- midazolam are well-described (figureS3,S4), and the intrinsic clearance values lead to total plasma clearance and bioavail- ability in range with previous published work (28,38,39), the intestinal and hepatic intrinsic clearance values are indeed well-estimated by the model and could therefore be used as surrogate marker for gut wall and hepatic CYP3A activity in children. As hepatic CYP3A4 is the most abundance cyto- chrome P450 enzyme and responsible for metabolism of a wide variety of therapeutics, the observed midazolam clear- ance as probe for CYP3A activity may have implications for other CYP3A substrates as well. It is also clinically relevant for patients receiving multiple CYP3A substrates or inhibitors/

enhancers as different drug-drug interactions in children versus adults may be anticipated. However, as the variability in oral bioavailability is very high, a highly variable drug exposure may be anticipated when CYP3A substrates are orally administered.

To conclude, this is the first study in children 1–18 years of age to distinguish between pediatric intestinal and hepatic CYP3A-mediated metabolism using clinical data together with PBPK principles. The results show that the whole- organ intrinsic hepatic clearance appears much higher than the gut wall clearance, but also that the difference between the whole-organ intrinsic clearances in children is smaller com- pared to adults. As a result, the intrinsic CYP3A-mediated gut wall clearance in children from 1 to 18 years of age con- tributes less to the overall first-pass metabolism compared to adults. Organ growth is the most important contributing fac- tor to the increase in the whole-organ intrinsic CYP3A clear- ance in gut wall and liver with age, given the fact that the intestinal CYP3A activity per gram of organ remained rela- tively constant throughout childhood and the hepatic CYP3A activity per gram of liver even decreased slightly. While intes- tinal bioavailability decreased with age, the hepatic bioavail- ability increased with age, resulting in no change in total bio- availability in children with increasing age and body weight.

This indicates an age-independent but highly variable first- pass effect by intestinal and hepatic CYP3A enzymes in chil- dren from 1 to 18 years of age.

ACKNOWLEDGMENTS AND DISCLOSURES

CAJ Knibbe was supported by an NWO Vidi grant (Knibbe 2013). The authors would like to thank Anthony Gebhart (LACDR, Leiden University) for the code review. Drs. Jeff Galinken and Peter Adamson were the PIs on the original study conducted at CHOP and the study was supported by NIH / NICHD, Pediatric Pharmacology Research Unit, Grant # HD037255–06.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which per- mits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

REFERENCES

1. Debotton N, Dahan A. A mechanistic approach to understanding oral drug absorption in pediatrics: an overview of fundamentals.

Drug Discov Today. 2014;19(9):1322–36.

2. Bai JPF, Burckart GJ, Mulberg AE. Literature review of gastroin- testinal physiology in the elderly, in pediatric patients, and in pa- tients with gastrointestinal diseases. J Pharm Sci. 2016;105(2):476–

83.

3. Mooij MG, de Koning BA, Huijsman ML, de Wildt SN. Ontogeny of oral drug absorption processes in children. Expert Opin Drug Metab Toxicol. 2012;8(10):1293–303.

References

Related documents

The exposure of these compounds to the Swedish population had not been studied before this project was performed, except for 11 samples from Swedish blood banks analysed by 3M

Insulin suppressed the effect of GH on hepatic triglyceride secretion rate and content, but this was not through changed gene expression of lipogenic enzymes or

Studies presented in this thesis work demonstrate that the transgenic mice overexpressing STK25 challenged with a high-fat diet display a shift in the metabolic balance in

This project focuses on the possible impact of (collaborative and non-collaborative) R&amp;D grants on technological and industrial diversification in regions, while controlling

Analysen visar också att FoU-bidrag med krav på samverkan i högre grad än när det inte är ett krav, ökar regioners benägenhet att diversifiera till nya branscher och

Parallellmarknader innebär dock inte en drivkraft för en grön omställning Ökad andel direktförsäljning räddar många lokala producenter och kan tyckas utgöra en drivkraft

If the aim of a PBPK model is extrapolation to the pediatric population, it must either firstly describe the adult data well and include data on all developmental changes affecting

The single sample plasma clearance method based on the mean sojourn time of a GFR marker in its distribution volume had previously been validated for determination of 99m Tc-